Recent weather fluctuations and agricultural yields: implications for climate change

We summarize recent statistical analyses that link agricultural yields to weather fluctuations. Similar to other sectors, high temperatures play a crucial role in predicting outcomes. Climate change is predicted to significantly increase high temperatures and thereby reduce yields. How good are such models at predicting future outcomes? We show that a statistical model estimated using historic US data on corn and soybean yields from 1950 to 2011 is very capable of predicting aggregate US yields for the years 2012–2015, where 2012 was much hotter than normal and is expected to become the new normal under climate change. We conclude by discussing recent studies on the implication of predicted yield declines with a special focus on adaptation and commodity prices.     

Agriculture and climate change in global scenarios: why don't the models agree

Agriculture is unique among economic sectors in the nature of impacts from climate change. The production activity that transforms inputs into agricultural outputs involves direct use of weather inputs (temperature, solar radiation available to the plant, and precipitation). Previous studies of the impacts of climate change on agriculture have reported substantial differences in outcomes such as prices, production, and trade arising from differences in model inputs and model specification. This article presents climate change results and underlying determinants from a model comparison exercise with 10 of the leading global economic models that include significant representation of agriculture. By harmonizing key drivers that include climate change effects, differences in model outcomes were reduced. The particular choice of climate change drivers for this comparison activity results in large and negative productivity effects. All models respond with higher prices. Producer behavior differs by model with some emphasizing area response and others yield response. Demand response is least important. The differences reflect both differences in model specification and perspectives on the future. The results from this study highlight the need to more fully compare the deep model parameters, to generate a call for a combination of econometric and validation studies to narrow the degree of uncertainty and variability in these parameters and to move to Monte Carlo type simulations to better map the contours of economic uncertainty.     

Modeling climate change and agriculture: an introduction to the special issue

This issue of Agricultural Economics is a special issue containing articles on model performance in assessing the effects of climate change, bioenergy policy, and socioeconomics on agriculture. The contributions present results from a global economic model intercomparison activity undertaken as part of the AgMIP Project ( www.agmip.org ). The origins of the comparison activities can be traced to a project that was organized by the OECD in late 2010 to compare results from three models. The current phase of the research includes 10 models and was designed in part to support of the IPCC fifth assessment report (AR5). The special issue includes seven peer‐reviewed articles that present thematic results from a range of modeling strategies, with partial and general equilibrium modeling as a high level distinction but a myriad of differences within these two model types. A central common element is harmonization on biophysical effects using crop models and socioeconomic effects using drivers from the Shared Socioeconomic Pathways developed as part of the AR5 process. The special issue provides broad insights into how the modeling communities approached the interactions of climate, socioeconomics, bioenergy policy on agricultural outcomes, including land use, prices, consumption, and production.     

The research cost of adapting agriculture to climate change: A global analysis to 2050

Investments in agricultural research and development (R&D) made over the next few decades will likely prove critical in offsetting adverse climate change impacts on the global food system. In this study, we offer cost estimates of public R&D-led adaptation to climate change grounded in an explicit framework relating the flow of annual R&D expenditures to building knowledge capital and thereby raising productivity in agriculture. Our research uses a comprehensive collection of historical public agricultural R&D expenditure and a literature review of elasticity estimates linking knowledge stocks to agricultural productivity growth for key world regions. Given climate-driven crop yield projections generated from extreme combinations of crop and global circulation models, we find that offsetting crop yield losses projected by climate and crop models over 2006–2050 would require increased R&D adaptation investments of between $187 billion and $1,384 billion (in 2005 $PPP) if we invest between 2020 and 2040. This is 16–118% higher than global R&D investment if present spending trends continue. Although these costs are significant, worldwide R&D-led climate adaptation could offer favorable economic returns. Moreover, R&D-led adaptation could deliver gains in food security and environmental sustainability by mitigating food price increases and slowing cropland expansion.     

Climate change: scenarios,impacts, policy,and development opportunities

This article is divided into three parts. First, it provides an overview of the main outcomes of the last IPCC assessment report, both in terms of economic drivers of greenhouse gas (GHG) emissions, and in terms of impacts of climate change, in particular for the agriculture sector. Then, it focuses on policy options and their optimal design, taking into account technological availability, international cooperation, and above all the stringency of the remaining carbon budget. Finally, it analyzes the size and direction of investment decisions required to stabilize GHG emissions and their implications for economic development.     

Impacts of considering climate variability on investment decisions in Ethiopia

Extreme interannual variability of precipitation within Ethiopia is not uncommon, inducing droughts or floods and often creating serious repercussions on agricultural and nonagricultural commodities. A dynamic climate module is integrated into an economy‐wide model containing a detailed zonal level agricultural structure. This coupled climate‐economic model is used to evaluate the effects of climate variability on prospective irrigation and infrastructure investment strategies, and the ensuing country‐wide economy. The linkages between the dynamic climate module and the economic model are created by the introduction of a climate‐yield factor (CYF), defined at the crop level and varied across Ethiopian zones. Nine sets of variable climate (VC) data are processed by the coupled model, generating stochastic wet and dry shocks, producing an ensemble of potential economic prediction indicators. Analysis of gross domestic product and poverty rate reveal a significant overestimation of the country's future welfare under all investment strategies when climate variability is ignored. The coupled model ensemble is further utilized for risk assessment to guide Ethiopian policy and planning.     

Modeling linkages between climate policy and land use: an overview

Agriculture and forestry play an important role in emitting and storing greenhouse gases. For an efficient and cost-effective climate policy, it is therefore important to include land use, land-use change, and forestry (LULUCF) explicitly in economy-climate models. This article gives an overview and assessment of existing approaches to include LULUCF into partial and general equilibrium economy-climate models. For each class of models, we describe different examples, their treatment of land, and their potential for and applicability to policy analysis, as well as their shortcomings. We identify data requirements and conceptual problems, and provide suggestions for future research.     

The economic impacts of technology and climate change: New evidence from U.S. corn yields

Over the past century, U.S. farmers have been offered a steady stream of new agricultural technologies, and more recently, experienced climate change. Because these two events have been occurring simultaneously, identifying their separate effects is difficult, and misimputation is easy. This article explicitly examines the economics of technical change and the interaction between weather and technology as revealed in a half century of panel data on U.S. Midwest rainfed state‐average corn yields. Observed yields reflect two components: yield potential and damage to the potential caused by weather and pests. Yield potential is modeled as a stochastic production frontier where nitrogen fertilization, public corn research, and introduction and adoption of biotech corn seeds impact yield potential and excess heat impacts nitrogen productivity. The yield‐damage/damage‐control function permits biotech corn plants to abate adverse effects of weather and pest events. Results include the following: nitrogen use, public corn research, and biotech seed‐corn adoption increase yield potential; soil moisture stress reduces yield potential, and excess heat severely reduces nitrogen productivity. Biotech corn plants abate yield damage caused by soil moisture stress but not excess heat.     

Warming temperatures will likely induce higher premium rates and government outlays for the U.S. crop insurance program

Likely climate change impacts include damages to agricultural production resulting from increased exposure to extreme heat. Considerable uncertainty remains regarding impacts on crop insurance programs. We utilize a panel of U.S. corn yield data to predict the effect of warming temperatures on the mean and variance of yields, as well as crop insurance premium rates and producer subsidies. While we focus on corn, we demonstrate that the subsidy impacts are likely to carry over to other major program crops. We find that warming decreases mean yields and increases yield risk on average, which results in higher premium rates. Under a 1°C warming scenario, we find that premium rates at the 90% coverage level will increase by 39% on average; however, there is considerable statistical uncertainty around this average as the 95% confidence interval spans from 22% to 61%. We also find evidence of extensive cross‐sectional differences as the county‐level rate impacts range from a 10% reduction to a 63% increase. Results indicate that exposure to extreme heat and changes in the coefficient of variation are large drivers of the impacts. Under the 1°C warming scenario, we find that annual subsidy payments for the crop insurance program could increase by as much as $1.5 billion, representing a 22% increase relative to current levels. This estimate increases to 3.7 billion (57%) under a 2°C warming scenario. Our results correspond to a very specific counterfactual: the marginal effect of warming temperatures under current technology, production, and crop insurance enrollments. These impacts are shown to be smaller than the forecasted impacts under a commonly used end‐of‐century general circulation model for even the most optimistic CO₂ emissions projection.     

The future of food demand: understanding differences in global economic models

Understanding the capacity of agricultural systems to feed the world population under climate change requires projecting future food demand. This article reviews demand modeling approaches from 10 global economic models participating in the Agricultural Model Intercomparison and Improvement Project (AgMIP). We compare food demand projections in 2050 for various regions and agricultural products under harmonized scenarios of socioeconomic development, climate change, and bioenergy expansion. In the reference scenario (SSP2), food demand increases by 59–98% between 2005 and 2050, slightly higher than the most recent FAO projection of 54% from 2005/2007. The range of results is large, in particular for animal calories (between 61% and 144%), caused by differences in demand systems specifications, and in income and price elasticities. The results are more sensitive to socioeconomic assumptions than to climate change or bioenergy scenarios. When considering a world with higher population and lower economic growth (SSP3), consumption per capita drops on average by 9% for crops and 18% for livestock. The maximum effect of climate change on calorie availability is ?6% at the global level, and the effect of biofuel production on calorie availability is even smaller.     

Property rights of urban underground space in China: A public good perspective

With the booming development of urban underground space in China, “fuzzy” property rights of this special form of land use type are not only the cause of ownership disputation and registration chaos, but also may seriously delay the undertaking of related underground land laws or regulations. China's emerging property rights issue of urban underground space, especially the delimitation of the surface and ground or underground, is facing such a challenge. This article aims to identify the property rights of urban underground space by using a practical method that classifies the underground space as economic goods, and to analyze attributes of different property rights of urban underground space within the theoretical framework of public goods. We use civil defense projects and underground parking lots as case studies. Both case studies are the most utilized types and controversial ownership cases of urban underground space in present China. Our case studies indicate that it is a feasible method to avoid the delimitation of the start-stop height of 3D property right vertically, and directly define the attributes of surface and underground property rights in line with the supply mode of goods. Our results show that the method proposed in this study can effectively solve the dispute of property rights against problems rising with unclear contract and lags in the legislation of urban underground space and clearly delimited the interests boundaries among different parties of property rights for urban underground space. Ultimately, this study may offer better insight into the utilization and registration work of urban underground space in China as well as reference for countries with similar property rights issues.     

Competition for land in the global bioeconomy

The global land use implications of biofuel expansion have received considerable attention in the literature over the past decade. Model‐based estimates of the emissions from cropland expansion have been used to assess the environmental impacts of biofuel policies. And integrated assessment models have estimated the potential for biofuels to contribute to greenhouse gas (GHG) abatement over the coming century. All of these studies feature, explicitly or implicitly, competition between biofuel feed stocks and other land uses. However, the economic mechanisms governing this competition, as well as the contribution of biofuels to global land use change, have not received the close scrutiny that they deserve. The purpose of this article is to offer a deeper look at these factors. We begin with a comparative static analysis which assesses the impact of exogenously specified forecasts of biofuel expansion over the period: 2006–2035. Global land use change is decomposed according to the three key margins of economic response: extensive supply, intensive supply, and demand. Under the International Energy Agency's “New Policies” scenario, biofuels account for nearly one‐fifth of global land use change over the 2006–2035 period. The article also offers a comparative dynamic analysis which determines the optimal path for first and second generation biofuels over the course of the entire 21st century. In the absence of GHG regulation, the welfare‐maximizing path for global land use, in the face of 3% annual growth in oil prices, allocates 225 Mha to biofuel feed stocks by 2100, with the associated biofuels accounting for about 30% of global liquid fuel consumption. This area expansion is somewhat diminished by expected climate change impacts on agriculture, while it is significantly increased by an aggressive GHG emissions target and by advances in conversion efficiency of second generation biofuels.     

Who is resilient in Africa’s Green Revolution? Sustainable intensification and Climate Smart Agriculture in Rwanda

Under the banner of a "New Green Revolution for Africa," agricultural intensification programs aim to make smallholder agriculture more productive as well as "climate smart". As with Green Revolutions in Asia and Mexico, agricultural innovations (hybrid seeds, agronomic engineering, market linkages,and increased use of fertilizer and pesticides) are promoted as essential catalysts of agriculture-led economic growth. Intensification programs are now frequently linked to Climate Smart Agriculture (CSA), which attempts to build resilience and reduce greenhouse gas emissions while increasing crop yields. This article considers who and what is resilient in Africa’s Green Revolution. We report on a multi-season study of smallholder food producers' experiences with Rwanda’s Crop Intensification Program (CIP) and related policies that aim to commercialize subsistence agriculture while implementing CSA. . We suggest that there are fundamental limits to the climate resilience afforded by CSA and development efforts rooted in Green Revolution thinking. Our findings illustrate that such efforts foreground technology and management adjustments in ways that have reduced smallholder resilience by inhibiting sovereignty over land use, decreasing livelihood flexibility, and constricting resource access. We put forth that rural development policies could better promote climate-resilient livelihoods through: 1) adaptive governance that enables smallholder land use decision-making; 2) support for smallholder food producers’ existing agro-ecological strategies of intensification; 3) participatory approaches to visualize and correct for inequalities in local processes of social-ecological resilence Such considerations are paramount for meeting the United Nations Sustainable Development Goals and building climate-resilient food systems.     

Evaluating irrigation investments in Malawi: economy‐wide impacts under uncertainty and labor constraints

Irrigation expansion is critical to increase crop yields and mitigate effects from climate change in Sub‐Saharan Africa, but the low profitability has led to little irrigation investments in the region so far. Using an integrated modeling framework, we simultaneously evaluate the returns to irrigation arising from both economic and biophysical impact channels to understand what determines the profitability of irrigation in Malawi. Our results confirm that the returns to irrigation cannot cover the costs in Malawi. While labor‐intensive irrigation expansion leads to unfavorable structural change in the short‐run, the profitability hinges on low irrigated yields that fall far from expectations due to insufficient input use and crop management techniques. On the other hand, we find that the nonmonetary benefits of irrigation regarding higher food security, lower poverty, and reduced vulnerability to climate change make investments in irrigation worthwhile to improve the livelihoods of smallholders.     

The fourth industrial revolution,agricultural and rural innovation,and implications for public policy and investments: a case of India

The Indian Government and public–private partnerships are developing and disseminating a dizzying number of innovative, networked solutions, broadly known as the Digital India initiative, to increase the efficiency of safety nets and worker productivity and to improve life. Yet, challenges to turn the power of information and other technologies into a farmer‐friendly technological revolution for India's 156 million rural households are considerable, including: (1) reliable, up‐to‐date, location‐specific message content for a diverse agriculture to help stratified households shift to productive, knowledge‐intensive agriculture as a business—government, private sector, and civil society have big roles to play; (2) digital literacy, i.e., teaching farmers how to choose and use apps, even where the digital divide is absent; apps are, or soon to be, in regional languages; and (3) monitoring actual use and impacts on users’ lives by understanding the adoption and adaptation processes. These challenges call for bottom‐up, complementary investments in physical, human, and institutional capital, and farmer‐friendly e‐platforms, while forging ahead with many top‐down policy and institutional reforms currently underway, in which progress is real and constraints holding back greater success are better understood.     

Evidence of climate change impacts on crop comparative advantage and land use

Relative agricultural productivity shocks emerging from climate change will alter regional cropland use. Land allocations are sensitive to crop profits that in turn depend on yield effects induced by changes in climate and technology. We develop and apply an integrated framework to assess the impact of climate change on agricultural productivity and land use for the U.S. Northern Great Plains. Crop-specific yield–weather models reveal crop comparative advantage due to differential yield impacts of weather across the region's major crops, that is, alfalfa, wheat, soybeans, and maize. We define crop profits as a function of the weather-driven yields, which are then used to model land use allocation decisions. This ultimately allows us to simulate the impact of climate change under the RCP4.5 emissions scenario on land allocated to the region's major crops as well as to grass/pasture. Upon removing the trends effects in yields, climate change is projected to lower yields by 33–64% over 2031–2055 relative to 1981–2005, with soybean being the least and alfalfa the most affected crops. Yield projections applied to the land use model at present-day input costs and output prices reveals that Dakotas’ grass acreage will increase by up to 23%, displacing croplands. Wheat acreage is expected to increase by up to 54% in select southeastern counties of North Dakota and South Dakota, where maize/soy acreage had increased by up to 58% during 1995–2016.     

Productivity and efficiency impact of climate change and agroecology on Bangladesh agriculture

The paper estimates the impacts of climate change, agroecological and socio-economic characteristics on agricultural productivity and efficiency changes in Bangladesh agriculture using a rich panel dataset of 17 regions covering a period of 61-years (1948–2008). Results revealed that land has the most dominant role in increasing agricultural production followed by labour and irrigation. The contribution of non-cereal crops (i.e., potatoes, pulses, oilseeds, jute and cash crops) to total production are also significant, ranging from 2 to 8% per annum. An increase in annual-rainfall and long-term-temperature (LTT) significantly enhance production. Production is significantly higher in floodplain agroecologies. However, production efficiency fluctuated sharply and declined overtime. The mean efficiency score of 0.74 implies substantial room to improve production by resource reallocation. Average farm size, crop specialization and investment in R&D significantly improve efficiency whereas increases in annual temperature-variability and LTT significantly reduce efficiency. Efficiency is significantly lower in low-lying floodplain and coastal-plain agroecologies. Policy implications include investments in diversifying cropping portfolio into other cereals (i.e., wheat and maize), research to develop crop varieties suited to changing climatic conditions and specific agroecological regions, and land/tenurial reforms to consolidate farm size to enhance productivity and efficiency of Bangladesh agriculture.     

Land‐use change trajectories up to 2050: insights from a global agro‐economic model comparison

Changes in agricultural land use have important implications for environmental services. Previous studies of agricultural land‐use futures have been published indicating large uncertainty due to different model assumptions and methodologies. In this article we present a first comprehensive comparison of global agro‐economic models that have harmonized drivers of population, GDP, and biophysical yields. The comparison allows us to ask two research questions: (1) How much cropland will be used under different socioeconomic and climate change scenarios? (2) How can differences in model results be explained? The comparison includes four partial and six general equilibrium models that differ in how they model land supply and amount of potentially available land. We analyze results of two different socioeconomic scenarios and three climate scenarios (one with constant climate). Most models (7 out of 10) project an increase of cropland of 10–25% by 2050 compared to 2005 (under constant climate), but one model projects a decrease. Pasture land expands in some models, which increase the treat on natural vegetation further. Across all models most of the cropland expansion takes place in South America and sub‐Saharan Africa. In general, the strongest differences in model results are related to differences in the costs of land expansion, the endogenous productivity responses, and the assumptions about potential cropland.     

Impacts of changing water inflow distributions on irrigation and farm income along the Drâa River in Morocco

Irrigation water is essential for agriculture in the arid Drâa River basin in Morocco but climate change leads to increasingly unreliable water supply in the area. This article analyzes impacts of changing water inflow distributions on irrigation and farm income extending a conjunctive river basin model toward a stochastic modeling approach. Regional climate scenarios are used to derive a maximum likelihood density estimate of current and future water supplies. Based on these distributions, Monte Carlo simulations are performed to obtain stochastic model results on surface and groundwater irrigation as well as economic indicators for six oases along the river. The probability of farmers to receive revenues below the subsistence level is around 2% under current conditions, but this is likely to rise to rates of 6% to 15% depending on the underlying climate change scenario. The composition of water sources for irrigation will shift to more groundwater use. The river basin model is able to represent complex spatial interactions between oases as well as a partial complementarity between groundwater and surface water irrigation due to salinity management effects. Interestingly, the value of groundwater is not necessarily increasing under future climatic conditions as salinity problems are aggravated with expanded groundwater use.